11min chapter

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ICLR 2024 — Best Papers & Talks (ImageGen, Vision, Transformers, State Space Models) ft. Durk Kingma, Christian Szegedy, Ilya Sutskever

Latent Space: The AI Engineer Podcast

CHAPTER

Unlocking Vision Transformers: Attention Maps Explored

This chapter focuses on the architecture of vision transformers and the critical role of attention maps in enhancing interpretability. It analyzes the behavior of outlier tokens and their surprising contribution to global information during image classification, as well as the innovative use of 'registers' to improve model performance. Through various datasets, the chapter highlights significant findings regarding accuracy and the evolving landscape of attention in visual processing.

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